Senior Software Developer Agentic AI Application Development
$100,000–$130,000 year
RemoteUnited States or Canada
Job Summary
Architect, build, and maintain applications integrating autonomous agents and large language models into end-to-end workflows. Design APIs, services, and event-driven components enabling agents to interact with systems, data, and users effectively. Pilot and integrate agent frameworks, orchestration layers, and multi-agent systems while automating repetitive tasks like code generation and testing. Define best practices for designing, deploying, and monitoring agentic workflows, coaching peers on prompt engineering and safe deployment. Conduct architecture reviews, mentor developers, and establish patterns for observability and human-in-the-loop validation. Deliver high-quality, scalable applications optimized for cost efficiency in cloud-native environments, owning the lifecycle from prototyping to production. Work in a small, high-impact team valuing experimentation and rapid iteration to shape how agentic applications are adopted in real-world settings.
Required Qualifications
- 5+ years of experience building and shipping production software systems
- Strong background in designing APIs, distributed systems, and event-driven architectures
- Proficiency in at least one statically typed language (Go, Java, C#) and one scripting language (Python, TypeScript, Bash)
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes)
- Demonstrated use of AI/LLM tooling in professional or side projects
- Curiosity and creativity in exploring agentic workflows and autonomous development approaches
- Strong communication skills and ability to collaborate across remote-first teams
- Remote within the United States or Canada (workday overlap from Pacific to Eastern time zones)
Desired Qualifications
- Experience with multi-agent frameworks, orchestration tools, or AI-powered application platforms
- Knowledge of service-mesh, observability tooling, and policy-as-code
- Familiarity with event-driven systems (Kafka, NATS) and domain-driven design
- Exposure to safety, ethics, and compliance considerations in AI systems
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